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A good principle of data analysis is never to fall in love with just one model.

-- McCullagh & Nelder, 1983 --

About us

In the Center for Statistics & Data Science led by Prof. Mirka Henninger, we evaluate and examine methodological and statistical procedures to analyze data in psychological research. Our research covers three main areas: psychometric modeling, machine learning methods, and the analysis of multilevel and longitudinal data.

We assess existing and develop new psychometric models in order to improve test fairness, measurement, and data quality. We also evaluate machine learning methods and interpretability techniques for their applicability in psychological research. Furthermore, we explore how multilevel data can be analyzed using psychometric models and methods from the machine learning framework.

Through our research, we facilitate advancements in the assessment of psychological characteristics and the optimal analysis of multivariate data within the field of psychology.